degenai: When I first started testing trading, the winning rate was very high, the decision was very fast, and the stop-loss and take-profit were strict, but in the past two days, I obviously felt that its trading ability had decreased, and many coins were not sold. I'm guessing it's a test pressure issue, but the team should find a way to fix it, after all, it's been so long to build.
Two days ago, when I used it, I told my friend to consider taking a 🤣 heavy position, which I would sell directly, on the grounds that I think it was a short-term sentiment. However, I personally think that it is possible to keep track of this project if it can re-do the trading side. And if 1m tokens can be used for robot trading, then ideally only 999 people can use this automated trading robot.
The short-term emotional premium is a bit big, and I hope to have the opportunity to pick me up in a gold pit, but now the most regrettable thing is that the 3m bias has not been studied much and ran 😭 directly
In the past couple of days, I had a deep experience with #degenai, and I was quite surprised by it.
This thing is essentially an on-chain subjective quantitative trading tool.
I dug into its entire trading logic, which has two built-in order logic systems: one is driven by a large model that feeds the model data such as sentiment, popularity, token trading, and price changes, and the large model makes decisions based on this;
The other uses traditional quantitative indicators, such as technical analysis, trading volume, and smart money wallet movements, which leans more towards traditional rational logic.
The combination of these two logic systems actually captures arbitrage opportunities during the spread of MEME sentiment. This approach is not about capturing all profits from trends but focuses on arbitraging during the most profitable, most certain, and lowest risk segments of volatility.
A good trading model must be like a vast river, only taking a sip from it.
From this perspective, DegenAi abstracts the human weaknesses on-chain into models and rules, and then executes trades through automation and algorithmic methods.
Compared to retail investors relying on intuition, gambling instincts, and speed in PVP, this fast in-and-out strategy based on sentiment spread, information time differences, and algorithmic advantages is the underlying logic that allows this quantitative model to outperform in the long run and truly establish itself.
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